Financial institutions are consistently trying to win new share.  There is a struggle to differentiate, when the key lever is always price.  Promising deals, offering low rates, giving cash back, the market is confused with messages that are differentiated from each other as they try to be innovative and unique.  
 
Spray and pray marketing has its place, but in this evolving landscape it’s more important than ever to make sure your message resonates at an individual customer level.

To answer this banks are profiling.  While data and analytics are a common practice to segmenting customers, profiling and targeting, the relevant legwork at the front is often ignored.  Fundamental to any marketing campaign is a solid understanding of what the customer wants, and although organisations frequently turn to panels for sentiment there are looming questions on the validity of the results: how robust was the methodology?  Were the participants a good demographical spread? Who is participating – those with time on their hands? All of these might bring about a sample that looks nothing like the customer you are trying to contract.

These qualitative results do have their merit, but for a truly comprehensive understanding quantitative results need to be thrown in the mix.    What does past purchasing behaviour look like? 

  • How do customers respond to campaigns regionally?  What are the differences?
  • What do different customer profiles look for?  A first home buyer typical buys in which suburb? With which characteristics? At what time of the year?
  • Pricing elasticity is normally an approach for different industries, but it has its place in the financial market – what rates / deals have made customers move? What rates have made no difference?
  • Which policies are important to the customer?
  • In the home buying process what is consistently difficult for the customer to understand?


By building a comprehensive dataset of past rates, uplift, regional behaviours, and buyer type traits, financial institutions will be one steps closer to defining what a customer truly needs and wants.  It can then differentiate its offering on this basis and be more in touch and engaging with its audience.

Adding to this, they must consistently measure the performance of their activities and ensure that they are capitalising on the learnings of what they have implemented.    The fundamental learning from all data and analytics rings true, first measure past, then undertake activity, then measure the outcome, so that you consistently optimise your budgets, resources and time and stay in tune with market movements.
 
Corelogic frequently assists financial institutions with quantitative results on how customers behave in the home buying / property financing process.  To find out about how we can help you, contact us now.